State-of-Art in the Age Determination of Venous Thromboembolism: A Systematic Review

Venous thromboembolism (VTE), consisting of deep vein thrombosis (DVT) and pulmonary embolism (PE), requires a forensic age determination to ascertain their causal relationship with recent events, such as trauma or medical treatment. The main objective of this systematic review is to identify the current state-of-the-art immunohistochemical methods for age determination of fatal VTE. A literature search was performed through different databases, according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Within the study, we have selected only cases represented by deceased patients for DVT and/or PTE in which thromboembolic material was collected during an autoptic examination and then subjected to a histological and an immunohistochemical investigation. Studies based on animal models were not included. We assessed bias risk. A database-based search produced a total of 19 articles. After excluding duplicate items from the selection, 14 articles were reviewed. Ten articles were excluded because they did not meet the inclusion criteria. The results have pointed out 4 studies that were included in the present analysis for a total of 157 samples of DVT and 171 PTE samples. These were analyzed using traditional histological and immunohistochemical techniques. The results must be interpreted with a critical eye because of their heterogeneity in terms of time, geography, and study design. The present review highlights the importance of associating specific immunohistochemical markers with a histological analysis for the timing of DVT/PTE fatal events. Further future experiences will hopefully endorse actual knowledge on the subject to increase the accuracy in the assessment of thrombus-embolus age.

Measuring of the COVID-19 Based on Time-Geography

At the end of 2019, the COVID-19 pandemic began to emerge on a global scale, including China, and left deep traces on all societies. The spread of this virus shows remarkable temporal and spatial characteristics. Therefore, analyzing and visualizing the characteristics of the COVID-19 pandemic are relevant to the current pressing need and have realistic significance. In this article, we constructed a new model based on time-geography to analyze the movement pattern of COVID-19 in Hebei Province. The results show that as time changed COVID-19 presented an obvious dynamic distribution in space. It gradually migrated from the southwest region of Hebei Province to the northeast region. The factors affecting the moving patterns may be the migration and flow of population between and within the province, the economic development level and the development of road traffic of each city. It can be divided into three stages in terms of time. The first stage is the gradual spread of the epidemic, the second is the full spread of the epidemic, and the third is the time and again of the epidemic. Finally, we can verify the accuracy of the model through the standard deviation ellipse and location entropy.

Car Use of the Carless in Sweden: Everyday Life Conditions for Reducing Car Dependence

For the sake of reducing car dependence, much can be learned from non-car owners about how everyday life can, and cannot, be organized without private car ownership. This study aims to explore carless mobility, including the role of the car, in relation to specific everyday projects and life situations. We do so through a descriptive analysis of data from the Swedish National Travel Survey 2011–2016, comparing carless mobility with that of car owners. Theoretically, our analysis builds on a constraints perspective with respect to mobility, which is rooted in time geography. We find that the constraints associated with activities and life situations seem to matter for how mobility is performed and for the feasibility of living a carless life. Managing the material flows of the household (for example, buying food and disposing of waste) is a project handled differently by non-car owners, through using nearby services and with a low degree of car use. On the other hand, our data suggest that maintaining social relations is car dependent and can potentially be more problematic for the carless. Moreover, an individual’s social network itself seems to be an important source of occasional car access. Results also indicate that the life situations of individuals may affect the mobility implications of carlessness, and the largest effect on trip frequency is found among carless retirees. From a planning perspective, and with the ambition to reduce private car use, this study identifies significant value in considering the different contexts of everyday life in which car use may or may not occur.

Analysis Of Youth Activities In The Digital Age: Time-Geographical Approach

The study analyses daily activities of youth in the virtual and actual environment within the framework of theoretical and applied achievements of time geography. The role of mobile devices in youth life, transformation of traditional activity and changes in the daily organization of actions due to digitalization are discussed. Empirical data for the research were obtained via a diary method (the respondents were 18–22-year-old students). Features of individual daily foreground and background activities, digital devices used, activities relation and localization are evaluated by geovisualization performed within the time-geographical concepts. Regardless of the smartphonization, individuals reserve time spans not associated with virtual activities; their online activities are localized within places of residence, study and traffic routes, while public spaces serve as “live communication” platforms (but a complete rejection of virtual activity does not occur here). An attempt to compare youth daily activity under ordinary conditions and during the period of forced isolation during the COVID-19 pandemic is being made.

Mobility during the COVID-19 Pandemic: A Data-Driven Time-Geographic Analysis of Health-Induced Mobility Changes

The COVID-19 pandemic has profoundly affected the spatial mobility of a major part of the population in many countries. For most people, this was an extremely disruptive shock, resulting in loss of income, social contact and quality of life. However, forced to reduce human physical interaction, most businesses, individuals and households developed new action lines and routines, and were gradually learning to adapt to the new reality. Some of these changes might result in long-term changes in opportunity structures and in spatial preferences for working, employment or residential location choice, and for mobility behavior. In this paper we aim to extend the time-geographic approach to analyzing people’s spatial activities, by focusing on health-related geographical mobility patterns during the pandemic in Sweden. Starting from a micro-approach at individual level and then looking at an aggregate urban scale, we examine the space-time geography during the coronavirus pandemic, using Hägerstrand’s time-geography model. We utilize a massive but (location-wise) fuzzy dataset to analyze aggregate spatiotemporal impacts of the COVID-19 pandemic using a contemporary time-geographical approach. First, we address micro-level behavior in time-space to understand the mechanisms of change and to illustrate that a temporal drastic change in human mobility seems to be plausible. Then we analyze the changes in individuals’ mobility by analyzing their activity spaces in aggregate using mobile phone network data records. Clearly, it is too early for predicting long-term spatial changes, but a clear heterogeneity in spatial behavior can already be detected. It seems plausible that the corona pandemic may have long-lasting effects on employment centers, city roles and spatial mobility patterns.

Political orientation and adherence to social distancing during the COVID-19 pandemic in Italy

Many governments have implemented social distancing and lockdown measures to curb the spread of the novel coronavirus (COVID-19). Using province-level geolocation data from Italy, we document that political disbelief can limit government policy effectiveness. Residents in provinces leaning towards extreme right-wing parties show lower rates of compliance with social distancing order. We also find that, during the Italian lockdown, provinces with high protest votes virtually disregarded all social distancing orders. On the contrary, in provinces with higher political support for the current political legislation, we found a higher degree of social distancing compliance. These results are robust to controlling for other factors, including time, geography, local COVID-19 cases and deaths, healthcare hospital beds, and other sociodemographic and economic characteristics. Our research shows that bipartisan support and national responsibility are essential to implement and manage social distancing efficiently. From a broader perspective, our findings suggest that partisan politics and discontent with the political class (i.e., protest voting) might significantly affect human health and the economy.